Distraction by deviant sounds is modulated by the environmental context

Evidence shows that participants performing a continuous visual categorization task respond slower following the presentation of a task-irrelevant sound deviating from an otherwise repetitive or predictable auditory context (deviant sound among standard sounds). Here, for the first time, we explored the role of the environmental context (instrumentalized as a task-irrelevant background picture) in this effect. In two experiments, participants categorized left/right arrows while ignoring irrelevant sounds and background pictures of forest and city scenes. While equiprobable across the task, sounds A and B were presented with probabilities of .882 and .118 in the forest context, respectively, and with the reversed probabilities in the city context. Hence, neither sound constituted a deviant sound at task-level, but each did within a specific context. In Experiment 1, where each environmental context (forest and city scene) consisted of a single picture each, participants were significantly slower in the visual task following the presentation of the sound that was unexpected within the current context (context-dependent distraction). Further analysis showed that the cognitive system reset its sensory predictions even for the first trial of a change in environmental context. In Experiment 2, the two contexts (forest and city) were implemented using sets of 32 pictures each, with the background picture changing on every trial. Here too, context-dependent deviance distraction was observed. However, participants took a trial to fully reset their sensory predictions upon a change in context. We conclude that irrelevant sounds are incidentally processed in association with the environmental context (even though these stimuli belong to different sensory modalities) and that sensory predictions are context-dependent.


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| (2022) 12:21447 | https://doi.org/10.1038/s41598-022-25500-y www.nature.com/scientificreports/ The latter would suggest that sensory predictions are unlikely to be underpinned solely by posterior sensory brain regions and might involve, instead, more frontal regions participating in the integration of information at higher levels of the cognitive architecture. Such a proposition is line with findings suggesting that the within-modality processing of information mostly mobilizes primary sensory cortices while cross-modal information involves more extensive frontal networks 62 , and fits well with the hierarchical organization of the brain [63][64][65] .
In this study, we carried out experiments in which participants categorized left/right symbols (" < " and " > ") while instructed to ignore a task-irrelevant background picture and a task-irrelevant sound presented immediately before each visual target (Fig. 1). The background pictures depicted a forest or a city scene. Two sounds (A & B) were used equiprobably across the task but with different conditional probabilities within each of these two visual contexts: in the forest context, sounds A and B were presented with probabilities of 0.882 and 0.118 respectively, while in the city context, the opposite pattern was used. Under the context-independent hypothesis, task-irrelevant sounds should be processed relative to previous auditory events, such that only sounds construed as deviating from an otherwise predictable auditory stream should capture attention and lengthen response times in the primary visual task. In our experimental design, because sounds A and B are used with equal probabilities across the task, no sound should constitute a deviation and so response times should be similar for these two Figure 1. Schematic illustration of the task. The bottom part of the figure illustrates a sequence of runs sharing the same context (forest or city). The upper part illustrates the timeline of specific individual trials marked by black arrows). In each trial, a task-irrelevant background picture (environmental context consisting of the picture of a forest or a city scene) appeared and remained visible throughout the trial. This was followed by the presentation of a task-irrelevant sound (A or B), then by the appearance of the target stimuli (< or >), which participants categorized as pointing left or right. Sounds A and B, equiprobable across the task, consisted of 440 Hz and 1047 Hz sinewave tones (the allocation of these sound files to the sound conditions A and B was counterbalanced across participants). Within the forest context, sounds A and B were presented with probabilities of 0.882 and 0.118 respectively, while the reverse probabilities were used in the city context. Runs of 3 to 5 trials of the same context (forest or city) were presented in sequence (note that to avoid visual overcrowding of this figure, we display 3 pictures per run). In Experiment 1, these contexts consisted of a single picture each (randomly selected for each participant). In Experiment 2, the background picture changed on every trial, cycling through two sets of 32 randomly ordered pictures for each context (forest and city).

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| (2022) 12:21447 | https://doi.org/10.1038/s41598-022-25500-y www.nature.com/scientificreports/ sounds irrespective of the environmental context. In contrast, according to the context-dependent hypothesis, task-irrelevant sounds should be appraised in relation to other elements of the task such as the environmental context, such that a sound should constitute a deviation whenever it violates sensory predictions within that context. If so, one sound (e.g., A) should elicit longer response times than the other (e.g., B) in the context in which A and B constitute deviant and standard sounds respectively.

Analyses
In Experiments 1 and 2, we analyzed the mean proportion of correct responses and the mean response times (RTs) for correct responses. Effect sizes are reported as partial eta-square values for F tests, and as Cohen's d az for within-participant comparisons 66 . All t-tests were two-tailed, except in the comparison of distraction between Experiments 1 and 2, where we explicitly specify that a one-tailed test was used. In addition to frequentist statistics, we also report the Bayes Factor (BF 10 ) to assess the credibility of the experimental hypothesis relative to that of the null hypothesis given the data. Values below 1/3 are considered as substantial to strong support for the null effect, while values above 3 are regarded as substantial to strong support for the presence of an effect 67,68 . Trials with response times faster than 200 ms were treated as anticipations and excluded from the analysis.
Temporal dynamics across same context runs. A follow-up analysis was carried out to examine the temporal dynamics of distraction across runs of trials involving the same context (forest or city). Such runs contained 3 to 5 trials and always started with a trial in which the sound presented corresponded to the standard sound within the context in question. The aim of this analysis was to determine how quickly the cognitive system reconfigured its auditory predictions upon a change in environmental context. More specifically, it allowed us to determine how a sound that recently acted as a deviant sound in one context (e.g., sound B in the forest context) was processed when constituting a standard sound in the newly changed context (e.g., sound B in the city context).
The analysis was carried out in two steps. First, we compared the mean performance in the first trial of a run (always standard; STD1) to the second trial (standard or deviant; STD2 or DEV2 respectively). Second, mean performance in trials 2 to 4 of a run were analyzed using a 2 (Sound Condition: standard vs deviant) × 4 (Position: trial 2-5 within a run) ANOVA for repeated measures. These analyses were carried out on both dependent variables (proportion correct and RTs, with the second being of primary interest).

Discussion
The results of Experiment 1 are unambiguous: The impact of task-irrelevant sounds occurring with equal probabilities across the task was modulated by their relationship with the environmental context (here instrumentalized as a task-irrelevant picture of a forest or of a city scene). Task-irrelevant sounds acquired the status of a deviant or a standard sound dependent upon their predictability given the environmental context, such that one sound became distractive relative to the other within one context (e.g., forest scene) while the reverse relationship was observed in the other context (city scene). This finding indicates that participants process the task-irrelevant sound as part of a more global context, integrating information across sensory modalities, even though the primary task made no demand on the auditory modality. Upon a change of context (e.g., forest scene to a city scene), the cognitive system updated its predictions in a context-dependent manner. This updating was completed within 200 ms from the onset of the picture. Indeed, we observed that a sound acting as a deviant sound and yielding longer RTs within one context did not do so on the very first trial following a change of context. While the implementation of the environmental context inspired from previous work using visual search tasks 54,55 proved efficient in our simple left-right categorization task, it is interesting to reflect upon the nature of this environmental context. In Experiment 1, this context consisted of two fixed visual scenes across the task 54 , though in our experiment the selection of the pictures varied across participants, as in previous work 55 .   www.nature.com/scientificreports/ Hence, the sounds may have been associated with any, or several, of many features characterizing the context: its visual features (e.g., colors, shapes, geometrical aspects) or its lexico-semantic features (interpretation of the scene as that of a forest or of that of a city scene, with all its possible ramifications). Our manipulation certainly contributed to establish solid and distinct environmental contexts. Yet, given the results from Experiment 1 and the apparent speed with which the cognitive system updates its sensory predictions, it would be interesting to examine whether the heterogeneity of the environmental context can influence the sound-context association by putting participants to the test using environmental contexts that are perceptually changing but categorically stable. We explored this issue in Experiment 2 by modifying our task to use sets of forest and city scenes and, while maintaining runs of 3 to 5 trials of a same context, varying the background picture on every trial. In doing so, we aimed to establish whether the cognitive system can differentiate between the two contexts in the face of constantly changing perceptual features. If it can, we aimed to examine how quickly the cognitive system updates its sensory predictions after a change of context.

Experiment 2
Results. Deviance distraction as a function of visual context. The mean proportion of correct responses (see Table 1) was analyzed using a 2 (Context: forest vs city) × 2 (Sound: Temporal dynamics across same context runs. The mean proportion of correct responses (see Table 1 Fig. 3B. In summary, a sound acting as a deviant sound and slowing responses within the previous context, remained distracting on its first occurrence as a standard sound within the new context. However, from the second trial in each run, the standard and deviant sounds for the new context diverged in their response times, consistent with the influence of the changed context. Comparing fixed versus varying contexts. Experiment 2 differed from Experiment 1 in that it involved many pictures in each of the two environmental contexts (forest and city). To assess whether the two types of manipulation differed with respect to the processing of the environmental context information, we compared the deviance distraction effect between the two experiments. To do so, we computed the mean distraction observed in each context (forest: RT SoundB -RT SoundA ; city: RT SoundA -RT SoundB ) and tested the hypothesis that contextspecific distraction by the unexpected sound should be greater when this context is defined by a single picture as opposed to several pictures (one-tailed t-test). The context-dependent distraction effect was significantly larger for the fixed context (M = 8.945, SD = 8.302) than for the varying context (M = 5.766, SD = 6.953), t(106) = 2.149, p = 0.017, d = 0.414 (95%CI 0.093 to infinity), BF 10 = 3.077.

Discussion
The results of Experiment 2 were clear-cut: The impact of the task-irrelevant sounds was again modulated by the environmental context. Slower responses were observed in the visual categorization task in trials involving the sound that was least expected within a specific context. Put differently, the same sound produced shorter response times within the context in which it was predictable relative to that in which it was not. Remarkably, this was observed despite a change of background picture on every trial. This may indicate that participants extracted semantic information from each picture, or that they extracted common information from multiple pictures of the same type of context. Whichever is the case, the data demonstrate that the contextual modulation of deviance distraction is not limited to the associative learning of sounds and specific pictures. In contrast to Experiment 1, the analysis of the temporal dynamics of this effect in Experiment 2 revealed that the reconfiguration of sensory predictions was slower than when contexts were defined by single pictures. Indeed, in Experiment 2, response times in the first standard trial following a change of context (e.g., from forest to city) were slower than in other standard trials and equivalent to those observed for deviant trials within the same context. In other words, a sound that constituted a deviant sound in a recent context (e.g., forest) still exerted distraction when first presented as the standard sound in the other context (e.g., city), and not thereafter. www.nature.com/scientificreports/ General discussion. In this study, we sought to examine whether task-irrelevant sounds are processed in relation to contextual elements of the task. More specifically, we investigated the extent to which sounds that are equally probable across the task would yield distraction when they constitute deviant sounds within a given environmental context (instrumentalized as a picture displayed as a task-irrelevant background in the primary visual task). If auditory predictions were generated on the basis of modality-specific information and were, therefore, independent from the visual context, performance in the categorization task should have remained stable irrespective of combination of sound and environmental context. Our results clearly departed from this prediction and, instead, support the hypothesis that sounds, although equiprobable across the task, do act as deviant and standard sounds depending on their conditional probabilities within a given environmental context. In Experiment 1, our environmental contexts consisted of two pictures: one of a forest and one of a city. The results confirmed that sensory predictions are generated in a context-dependent manner, such that the sound rarely presented within one specific context yielded longer response times in the primary task relative to the sound frequently associated with that same context. The analysis of this effect across runs of trials of the same context revealed that the cognitive system was capable of reconfiguring its sensory predictions on the very first trial following a change of environmental context. More specifically, this reconfiguration was completed within the 200 ms window during which the visual background was visible ahead of the presentation of the sound. In Experiment 2, the forest and city contexts were implemented using a large set of pictures that changed on every trial. Despite the constant change of background picture, the main result was identical to that of Experiment 1: Longer RTs were observed in the primary task in the presence of a task-irrelevant sound when this sound's probability of occurrence was low in a given context (forest vs city) relative to a sound that was highly probable within that context. However, a subsequent analysis revealed that, in contrast to Experiment 1, participants took relatively longer to reconfigure their sensory predictions, such that the sound most likely to occur within a given context did produce distraction on the very first trial following a change of context. In other words, when the environmental context is defined categorically rather than by a specific picture, the context-dependent reconfiguration of predictions appears to require more time.
Evidence from object recognition and detection studies using visual scenes as environmental context indicates that semantic aspects of these scenes are processed automatically and rapidly, including under subliminal presentation times [69][70][71][72][73] . Participants are certainly capable of understanding a visual scene with exposure durations of about 100 ms 69,74,75 and to extract contextual semantic information in as little as 80 ms 76 . In our experiments, while our visual scenes were more complex that single objects, their appearance 200 ms ahead of the sound's onset should have allowed participants sufficient time to process the contextual information and distinguish one context from the other. Yet our results suggest that the environmental context and its statistical relation to the task-irrelevant sound may involve different mechanisms when context is defined by a single picture (Experiment 1) compared to varying pictures (Experiment 2). Indeed, in Experiment 2 we observed less deviance distraction and a slower updating of sensory predictions. A context defined by a fixed picture affords constant perceptual (shapes, configuration of elements, colors, etc.) and semantic features, thereby maximizing the amount of information available to the cognitive system to identity and learn that context. One possibility is that the cognitive system combines all of these features in the representation of the context in relation to the task-irrelevant sounds. However, this does not necessarily need to be the case, for one may argue that a fast and efficient way to process constant contextual information would be to limit it to low-level visual features (since these are presumably processed fastest). When the context consists of a fixed picture, such information is sufficient to distinguish it from an alternative context. What is clear, however, is that in the case of contexts defined by varying pictures, context-dependent effects must necessarily involve the extraction of features common to these pictures. Such features may be perceptual, for these pictures would, for example, share certain color schemes (forests tend to be characterized by green, brown, yellow and red tones, while city scenes are more likely to contain other tones, such as grays or blues) or geometrical arrangements (forests contain several vertically oriented elements such as tree trunks and are dominated by texture zones and undulating contours, while city scenes tend to be characterized by straight lines 77,78 ). The information extracted may also be categorical (lexico-semantic), freeing the context from its sensory features and rendering it more abstract. Whichever type of information is extracted, one advantage of such abstraction would be to process environmental contexts in a more flexible manner, allowing for changes in the scenes while preserving the context's coherence. It is interesting to note that research on a different type of visual stimuli, namely human faces, has shown that participants seem to encode the average of such stimuli with respect to aspects such as emotional expression 79 , gender 80 or gaze direction 81 . Such extraction of summary statistics has been observed with both familiar 82 and unfamiliar 83 faces. One aspect worth considering is the distinction between the extraction of information from a visual context and the categorization of this context. While evidence suggests that participants presented with very brief (94 ms) black and white pictures depicting natural (e.g., forest, river) or man-made scenes (e.g., house, construction) are capable of categorizing these correctly 84 , such a task differs from ours in that it explicitly requires participants to attend to and categorize visual scenes. In our experiment, the environmental context was incidental to the task and participants were encouraged to ignore it to focus on the target stimulus. Interestingly, evidence based on multivariate pattern analysis of EEG signals indicates that the incidental categorization of color scenes such as roads, churches, houses and supermarkets, appears to take about 200 ms 85 . This suggests that in our Experiment 2, the categorization of our forest or city scenes would barely have been completed (or indeed on many occasions it may not have) by the time the taskirrelevant sound was presented. Under the reasonable assumption that the reconfiguration of sensory predictions would follow the categorization of the context (be it in perceptual and/or semantic terms, our position is agnostic in this respect), the sound would be processed ahead of this reconfiguration being completed. Hence, the environmental context would fail to trigger the reconfiguration of the predictions in time to complete the very first trial following a change of context. However, such reconfiguration would be completed by the next trial.

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| (2022) 12:21447 | https://doi.org/10.1038/s41598-022-25500-y www.nature.com/scientificreports/ In contrast, in Experiment 1, the reconfiguration could be achieved significantly faster because the use of a fixed picture per context rendered unnecessary the categorization of the context based on some abstracted information.
Our results provide further evidence that the environmental context is processed even when it is task-irrelevant and when the primary task makes no demand on explicit memory. Indeed, in contrast to past studies reporting the impact of the context of recall on recollection performance [44][45][46]50 , participants in our study simply categorized visual stimuli without any requirement to voluntarily encode any information for later recall. This suggests that the associative learning of task-relevant and task-irrelevant information and predictions generated upon it are not process-dependent. That is, the cognitive system need not be engaged in explicit memory processes for this learning to occur. In that respect, our results add to the limited evidence on the impact of the context on attentional tasks. Indeed, past work manipulating the environmental context in visual attention tasks 54,55 reported clear indications that visual search mechanisms are modulated by the reinstatement of information previously associated with specific contexts. In contrast to these studies, however, ours extended this demonstration to a cross-modal task. To our knowledge, our study constitutes the first demonstration of the cognitive system's associative learning of irrelevant visual information (environmental context) and irrelevant auditory information in the context of a visual primary task. This suggests that task elements, though irrelevant, are processed and bound at a level of cognitive hierarchy that supersedes sensory or modality-specific codes. Remarkably, this associative learning can involve a relatively complex abstraction of the context, as was the case when it is not defined by a single visual scene but by several, reinforcing the contention that this associative learning cannot be reduced to the binding of sensory information. When the context is abstracted, the cognitive system takes longer to adapt its predictions. This may reflect the time required to activate the abstracted context from a specific visual scene, and/or the longer time required to update auditory predictions when the impetus to do so emanates from higher levels in the cognitive architecture, referred to as "episodic control" by Koechlin et al. 63 , rather than from sensory control. Our study certainly opens avenues for future research, from a parametric exploration of the temporal dynamics of the context-dependent reconfiguration of sensory predictions (e.g., how long does the cognitive system take to update predictions?), to the further study of the mental representation of the environmental context (e.g., what is the nature of context abstraction when defined by multiple images?).
Finally, it is worth considering briefly some potential broader implications of our findings. We showed that task-irrelevant sounds are processed in relation to the environmental context, which we instrumentalized as a task-irrelevant background picture. However, environmental contexts arguably involve more than the screen background (e.g., the room, building or wider geographical context, or other circumstantial or episodic elements, such as the experience of participating in an experiment). Hence, our environmental context manipulation was only partial. This means that the actual impact of the environmental context on deviance distraction may potentially be stronger than the effect we measured in our experiments. By the same token, in past studies where the environmental context was not experimentally manipulated and all auditory stimuli were processed within the same broad context (e.g., constant screen background, room, etc.), it is possible that the effect of deviant sound (electrophysiological and/or behavioral) reported in these studies may have, at least partially, emerged through context-dependent mechanisms. Unsurprisingly, past studies have not considered this aspect. Yet, it presents certain implications, for it suggests that sensory predictions may not be solely underpinned by the activity of sensory, posterior, brain regions but may also involve links to the activity of other sensory regions (e.g., visual) and/ or higher (frontal) regions. Furthermore, our results may also possibly lead to the reinterpretation of some past findings. For example, several studies have concluded that the reduction of deviance distraction when standard and deviant sounds are preceded by visual cues reflect the intervention of cognitive control 34,35,86 . However, if the visual cue is interpreted as part of the environmental context, then this finding can be explained as a manifestation of the context-dependent processing of the auditory stimuli without the need to invoke cognitive control (the underpinning mechanisms of which past studies have not clearly delineated).
In summary, our study shows that participants performing a visual categorization task involuntarily process task-irrelevant stimuli and their relationship to the environmental context. As a result, the presentation of the latter appears to cue the updating of sensory predictions, thereby resulting in distraction when a given sound deviates from predictions. Our results indicate that task-irrelevant sounds are not only processed in relation to the auditory context (built over time and defined as past auditory stimuli 32,35,[87][88][89] ) but also, across sensory modalities, and rapidly, to the visual environmental context.  (46 females). Four participants were lefthanded. All were undergraduate psychology students who took part in the study in exchange for course credit.

Methods
Material and stimuli. A set of five forest scenes and five city scenes was built. These pictures were selected from a royalty-free photography repository (pixabay.com). Pictures were resized or cropped to a 1280 × 720 pixels dimension. None of the pictures contained prominent people, vehicles, or readable text.
The task was programmed using Psychology Software's E-Prime 3.0 software and was executed on a PC computer equipped with a 17in screen. Auditory stimuli were delivered binaurally with headphones, at an intensity of approximately 70 dB SPL. Participants were tested within a sound-attenuated cabin.
Procedure. Participants were asked to categorize the direction in which a target stimulus (" < " or " > ") pointed, while ignoring task-irrelevant sounds presented immediately before each target stimulus as well as pictures displayed in the background. www.nature.com/scientificreports/ Each trial began with the appearance of a background picture occupying the entire screen (referred to as context hereafter), and a fixation cross in white color in the middle of a centrally located black rectangle that occupied 13% of the screen's width and 18% of the screen's height. These stimuli remained visible throughout the trial, except when the target stimulus temporarily replaced the fixation cross (as described below). Following an interval of 200 ms, one of two task-irrelevant sinewave sounds (440 Hz or 1047 Hz) was presented for 200 ms. Upon the sound's offset, the target stimulus (" < " or " > ", in Arial font size 48) replaced the fixation cross for a duration of 200 ms, followed by a further interval of 800 ms before the next trial began automatically. A schematic illustration is presented in Fig. 1.
The choice and arrangement of the background pictures, sounds and target stimuli followed specific rules. Across the task, one forest picture and one city picture were used. For each participant, these pictures were selected randomly from respective sets of five pictures. The two selected pictures were used equiprobably as background pictures in runs of trials of 3 to 5 consecutive trials, creating a total of 1216 test trials. That is, there were 3-5 trials with one background picture, then 3-5 trials with the other background picture without any change in the continuity of trials, and so on in alternation. Among these forest and city trials, both target stimuli (" < " and " > ") were presented equally often. Two irrelevant sounds (440 Hz and 1047 Hz) were used equiprobably across the task but with distinct probabilities within each of the two contexts (forest vs city). One sound (e.g., 440 Hz) was more likely in one context (e.g., forest context) than the other (e.g., 1047 Hz): p = 0.882 and p = 0.118, respectively. These probabilities were reversed in the other context (e.g., city). Hence, while each sound was presented in half the trials across the task, it constituted a standard sound in one context (e.g., forest) and a deviant sound in the other (e.g., city). The allocation of the sounds (A and B) to the two contexts (forest and city) was counterbalanced across participants. Within a run of trials of the same context, sounds constituting a deviant within that context were never presented on the first trial of a run. Finally, only half of the runs of trials of a specific context involved a trial with a deviant sound (to avoid expectation effects). The 1216 test trials were divided into 4 blocks of 304 trials lasting about 7 min each (participants were allowed to pause for a few seconds before resuming the task).
Before participants completed the 4 blocks of test trials, they performed a block of 10 practice trials in which no sound or background picture was presented. Feedback was provided after each response in the form of text appearing during 1500 ms after the participant's response. This feedback indicated whether the response was correct, incorrect, or urged participants to respond faster if they failed to respond. This feedback was not presented in the rest of the experiment. Experiment 2. Participants. Fifty-eight psychology undergraduate students took part in this online study in exchange for course credit (none had taken part in Experiment 1). Six reported having been interrupted during the experiment and were removed from the sample, leaving 52 participants (42 females) aged 19 to 26 (M = 19.692, SD = 1.365). Six participants were lefthanded.
Material and stimuli. A set of 32 forest pictures and 32 street pictures was built. These pictures were selected from four royalty-free photography repositories (unplash.com, pixabay.com, freeimages.com, pixels.com). Where necessary, pictures were resized or cropped to a 1280 × 720 pixels dimension. None of the pictures contained people, vehicles, or readable text (in a few cases, this was achieved though airbrushing out some information).
Since this experiment was carried out online, the exact characteristics of the computers used to run the experiment, such as monitor size, is not known. The task was programmed using Psychology Software's E-Prime 3.0 software and deployed using EPrimeGo 1.0 (running on PC computers only). Participants were instructed to wear headphones or, alternatively, use loudspeakers connected to their computer.
Procedure. The cross-modal oddball task followed the same design as in Experiment 1 with the following differences. Across the task, 32 forest pictures and 32 city pictures were used, with each picture used 19 times across the experiment. The order of presentation of these pictures was set so that each set of 32 pictures was used once (in random order) before a new random cycle was presented. The same picture was never presented on successive trials.
Since the task was administered online, it was not possible to control sound levels or equate them across participants. An audio-video introduction was presented at the beginning of the experiment inviting participants to wear headphones (or use loudspeakers) and set the sound level on their computer to a comfortable level. Sound checks were programmed within the task at the onset of the experiment and after the last trial of every block. These tests consisted in the presentation of a sequence of 3 auditory digits that participants were required to reproduce in order using the corresponding keys on their keyboards. Participants were told that these checks would take place at different moments during the experiments. These checks were implemented to reduce the risk that participants would turn the sound off.
Finally, at the end of the experiment, participants were asked to indicate whether they were interrupted while performing the experiment (data from participants who declared having been interrupted during the experiment were discarded from the analysis).
This study was carried out in accordance with the recommendations of American Psychological Association with written informed consent from all subjects. All subjects gave written informed consent in accordance with the Declaration of Helsinki. The protocol was approved by the Bioethical Committee of the University of the Balearic Islands.